Temporal evolution of "automatic gain-scaling"

Variable impact of tizanidine on the medium latency reflex of upper and lower limbs

Sudden limb displacement evokes a complex sequence of compensatory muscle activity. Following the short-latency reflex and preceding voluntary reactions is an epoch termed the medium-latency reflex (MLR) that could reflect spinal processing of group II muscle afferents. One way to test this possibility is oral ingestion of tizanidine, an alpha-2 adrenergic agonist that inhibits the interneurons transmitting group II signals onto spinal motor neurons. We examined whether group II afferents contribute to MLR activity throughout the major muscles that span the elbow and shoulder. MLRs of ankle muscles were also tested during walking on the same day, in the same participants as well as during sitting in a different group of subjects. In contrast to previous reports, the ingestion of tizanidine had minimal impact on MLRs of arm or leg muscles during motor actions. A significant decrease in magnitude was observed for 2/16 contrasts in arm muscles and 0/4 contrasts in leg muscles. This discrepancy with previous studies could indicate that tizanidine's efficacy is altered by subtle changes in protocol or that group II afferents do not substantially contribute to MLRs.

Mechanical perturbations can elicit triggered reactions in the absence of a startle response

Perturbations delivered to the upper limbs elicit reflexive responses in stretched muscle at short- (M1: 25-50 ms) and long- (M2: 50-100 ms) latencies. When presented in a simple reaction time (RT) task, the perturbation can also elicit a preprogrammed voluntary response at a latency (< 100 ms) that overlaps the M2 response. This early appearance of the voluntary response following a proprioceptive stimulus causing muscle stretch is called a triggered reaction. Recent work has demonstrated that a perturbation also elicits activity in sternocleidomastoid (SCM) over a time-course consistent with the startle response and it was, therefore, proposed that the StartReact effect underlies triggered reactions (Ravichandran et al., Exp Brain Res 230:59-69, 2013). The present work investigated whether perturbation-evoked SCM activity results from startle or postural control and whether triggered reactions can also occur in the absence of startle. In Experiment 1, participants "compensated" against a wrist extension perturbation. A prepulse inhibition (PPI) stimulus (known to attenuate startle) was randomly presented before the perturbation. Rather than attenuating SCM activity, the responses in SCM were advanced by the PPI stimulus. In Experiment 2, participants "assisted" a wrist extension perturbation. The perturbation did not reliably elicit startle but despite this, two-thirds of trials had RTs of less than 100 ms and the earliest responses began at ~ 70 ms. These findings suggest that SCM activity following a perturbation is the result of postural control and is not related to startle. Moreover, an overt startle response is not a prerequisite for the elicitation of a triggered reaction.

Perspectives on classical controversies about the motor cortex

Primary motor cortex has been studied for more than a century, yet a consensus on its functional contribution to movement control is still out of reach. In particular, there remains controversy as to the level of control produced by motor cortex ("low-level" movement dynamics vs. "high-level" movement kinematics) and the role of sensory feedback. In this review, we present different perspectives on the two following questions: What does activity in motor cortex reflect? and How do planned motor commands interact with incoming sensory feedback during movement? The four authors each present their independent views on how they think the primary motor cortex (M1) controls movement. At the end, we present a dialogue in which the authors synthesize their views and suggest possibilities for moving the field forward. While there is not yet a consensus on the role of M1 or sensory feedback in the control of upper limb movements, such dialogues are essential to take us closer to one.

Rapid visuomotor feedback gains are tuned to the task dynamics

Here, we test whether rapid visuomotor feedback responses are selectively tuned to the task dynamics. The responses do not exhibit gain scaling, but they do vary with the level and stability of task dynamics. Moreover, these feedback gains are independently tuned to perturbations to the left and right, depending on these dynamics. Our results demonstrate that the sensorimotor control system regulates the feedback gain as part of the adaptation process, tuning them appropriately to the environment.

Adaptation to novel dynamics requires learning a motor memory, or a new pattern of predictive feedforward motor commands. Recently, we demonstrated the upregulation of rapid visuomotor feedback gains early in curl force field learning, which decrease once a predictive motor memory is learned. However, even after learning is complete, these feedback gains are higher than those observed in the null field trials. Interestingly, these upregulated feedback gains in the curl field were not observed in a constant force field. Therefore, we suggest that adaptation also involves selectively tuning the feedback sensitivity of the sensorimotor control system to the environment. Here, we test this hypothesis by measuring the rapid visuomotor feedback gains after subjects adapt to a variety of novel dynamics generated by a robotic manipulandum in three experiments. To probe the feedback gains, we measured the magnitude of the motor response to rapid shifts in the visual location of the hand during reaching. While the feedback gain magnitude remained similar over a larger than a fourfold increase in constant background load, the feedback gains scaled with increasing lateral resistance and increasing instability. The third experiment demonstrated that the feedback gains could also be independently tuned to perturbations to the left and right, depending on the lateral resistance, demonstrating the fractionation of feedback gains to environmental dynamics. Our results show that the sensorimotor control system regulates the gain of the feedback system as part of the adaptation process to novel dynamics, appropriately tuning them to the environment.

NEW & NOTEWORTHY Here, we test whether rapid visuomotor feedback responses are selectively tuned to the task dynamics. The responses do not exhibit gain scaling, but they do vary with the level and stability of task dynamics. Moreover, these feedback gains are independently tuned to perturbations to the left and right, depending on these dynamics. Our results demonstrate that the sensorimotor control system regulates the feedback gain as part of the adaptation process, tuning them appropriately to the environment.

Multisensory components of rapid motor responses to fingertip loading

Tactile and muscle afferents provide critical sensory information for grasp control, yet the contribution of each sensory system during online control has not been clearly identified. More precisely, it is unknown how these two sensory systems participate in online control of digit forces following perturbations to held objects. To address this issue, we investigated motor responses in the context of fingertip loading, which parallels the impact of perturbations to held objects on finger motion and fingerpad deformation, and characterized surface recordings of intrinsic (first dorsal interosseous, FDI) and extrinsic (flexor digitorum superficialis, FDS) hand muscles based on statistical modeling. We designed a series of experiments probing the effects of peripheral stimulation with or without anesthesia of the finger, and of task instructions. Loading of the fingertip generated a motor response in FDI at ~60 ms following the perturbation onset, which was only driven by muscle stretch, as the ring-block anesthesia reduced the gain of the response occurring later than 90 ms, leaving responses occurring before this time unaffected. In contrast, the motor response in FDS was independent of the lateral motion of the finger. This response started at ~90 ms on average and was immediately adjusted to task demands. Altogether these results highlight how a rapid integration of partially distinct sensorimotor circuits supports rapid motor responses to fingertip loading.NEW & NOTEWORTHY To grasp and manipulate objects, the brain uses touch signals related to skin deformation as well as sensory information about motion of the fingers encoded in muscle spindles. Here we investigated how these two sensory systems contribute to feedback responses to perturbation applied to the fingertip. We found distinct response components, suggesting that each sensory system engages separate sensorimotor circuits with distinct functions and latencies.

Rapid and flexible whole body postural responses are evoked from perturbations to the upper limb during goal-directed reaching

An important aspect of motor control is the ability to perform tasks with the upper limbs while maintaining whole body balance. However, little is known about the coordination of upper limb voluntary and whole body postural control after mechanical disturbances that require both upper limb motor corrections to attain a behavioral goal and lower limb motor responses to maintain whole body balance. The present study identified the temporal organization of muscle responses and center of pressure (COP) changes following mechanical perturbations during reaching. Our results demonstrate that muscle responses in the upper limb are evoked first (∼50 ms), with lower limb muscle activity occurring immediately after, in as little as ∼60 ms after perturbation. Hand motion was immediately altered by the load, while COP changes occurred after ∼100 ms, when lower limb muscle activity was already present. Our secondary findings showed that both muscle activity and COP changes were influenced by behavioral context (by altering target shape, circle vs. rectangle). Voluntary and postural actions initially directed the hand toward the center of both target types, but after the perturbation upper limb and postural responses redirected the hand toward different spatial locations along the rectangle. Muscle activity was increased for both upper and lower limbs when correcting to the circle vs. the rectangle, and these differences emerged as early as the long-latency epoch (∼75-120 ms). Our results demonstrate that postural responses are rapidly and flexibly altered to consider the behavioral goal of the upper limb.NEW & NOTEWORTHY The present work establishes that, when reaching to a target while standing, perturbations applied to the upper limb elicit a rapid response in lower limb muscles. Unlike voluntary movements, postural responses do not occur before corrections of the upper limb. We show the first evidence that corrective postural adjustments are modulated by upper limb behavioral context (target shape). Importantly, this indicates that postural responses take into account upper limb feedback for online control.

Voluntary reaction time and long-latency reflex modulation

Stretching a muscle of the upper limb elicits short (M1) and long-latency (M2) reflexes. When the participant is instructed to actively compensate for a perturbation, M1 is usually unaffected and M2 increases in size and is followed by the voluntary response. It remains unclear if the observed increase in M2 is due to instruction-dependent gain modulation of the contributing reflex mechanism(s) or results from voluntary response superposition. The difficulty in delineating between these alternatives is due to the overlap between the voluntary response and the end of M2. The present study manipulated response accuracy and complexity to delay onset of the voluntary response and observed the corresponding influence on electromyographic activity during the M2 period. In all active conditions, M2 was larger compared with a passive condition where participants did not respond to the perturbation; moreover, these changes in M2 began early in the appearance of the response (∼ 50 ms), too early to be accounted for by voluntary overlap. Voluntary response latency influenced the latter portion of M2, with the largest activity seen when accuracy of limb position was not specified. However, when participants aimed for targets of different sizes or performed movements of various complexities, reaction time differences did not influence M2 period activity, suggesting voluntary activity was sufficiently delayed. Collectively, our results show that while a perturbation applied to the upper limbs can trigger a voluntary response at short latency (<100 ms), instruction-dependent reflex gain modulation remains an important contributor to EMG changes during the M2 period.

Goal-dependent modulation of the long-latency stretch response at the shoulder, elbow, and wrist

Many studies have demonstrated that muscle activity 50-100 ms after a mechanical perturbation (i.e., the long-latency stretch response) can be modulated in a manner that reflects voluntary motor control. These previous studies typically assessed modulation of the long-latency stretch response from individual muscles rather than how this response is concurrently modulated across multiple muscles. Here we investigated such concurrent modulation by having participants execute goal-directed reaches to visual targets after mechanical perturbations of the shoulder, elbow, or wrist while measuring activity from six muscles that articulate these joints. We found that shoulder, elbow, and wrist muscles displayed goal-dependent modulation of the long-latency stretch response, that the relative magnitude of participants' goal-dependent activity was similar across muscles, that the temporal onset of goal-dependent muscle activity was not reliably different across the three joints, and that shoulder muscles displayed goal-dependent activity appropriate for counteracting intersegmental dynamics. We also observed that the long-latency stretch response of wrist muscles displayed goal-dependent modulation after elbow perturbations and that the long-latency stretch response of elbow muscles displayed goal-dependent modulation after wrist perturbations. This pattern likely arises because motion at either joint could bring the hand to the visual target and suggests that the nervous system rapidly exploits such simple kinematic redundancy when processing sensory feedback to support goal-directed actions.

Human muscle spindle sensitivity reflects the balance of activity between antagonistic muscles

Muscle spindles are commonly considered as stretch receptors encoding movement, but the functional consequence of their efferent control has remained unclear. The "α-γ coactivation" hypothesis states that activity in a muscle is positively related to the output of its spindle afferents. However, in addition to the above, possible reciprocal inhibition of spindle controllers entails a negative relationship between contractile activity in one muscle and spindle afferent output from its antagonist. By recording spindle afferent responses from alert humans using microneurography, I show that spindle output does reflect antagonistic muscle balance. Specifically, regardless of identical kinematic profiles across active finger movements, stretch of the loaded antagonist muscle (i.e., extensor) was accompanied by increased afferent firing rates from this muscle compared with the baseline case of no constant external load. In contrast, spindle firing rates from the stretching antagonist were lowest when the agonist muscle powering movement (i.e., flexor) acted against an additional resistive load. Stepwise regressions confirmed that instantaneous velocity, extensor, and flexor muscle activity had a significant effect on spindle afferent responses, with flexor activity having a negative effect. Therefore, the results indicate that, as consequence of their efferent control, spindle sensitivity (gain) to muscle stretch reflects the balance of activity between antagonistic muscles rather than only the activity of the spindle-bearing muscle.

Long-latency reflexes account for limb biomechanics through several supraspinal pathways

Accurate control of body posture is enforced by a multitude of corrective actions operating over a range of time scales. The earliest correction is the short-latency reflex (SLR) which occurs between 20–45 ms following a sudden displacement of the limb and is generated entirely by spinal circuits. In contrast, voluntary reactions are generated by a highly distributed network but at a significantly longer delay after stimulus onset (greater than 100 ms). Between these two epochs is the long-latency reflex (LLR) (around 50–100 ms) which acts more rapidly than voluntary reactions but shares some supraspinal pathways and functional capabilities. In particular, the LLR accounts for the arm’s biomechanical properties rather than only responding to local muscle stretch like the SLR. This paper will review how the LLR accounts for the arm’s biomechanical properties and the supraspinal pathways supporting this ability. Relevant experimental paradigms include clinical studies, non-invasive brain stimulation, neural recordings in monkeys, and human behavioral studies. The sum of this effort indicates that primary motor cortex and reticular formation (RF) contribute to the LLR either by generating or scaling its structured response appropriate for the arm’s biomechanics whereas the cerebellum scales the magnitude of the feedback response. Additional putative pathways are discussed as well as potential research lines.

Nonlinear 2D arm dynamics in response to continuous and pulse-shaped force perturbations

Ample evidence exists regarding the nonlinearity of the neuromuscular system but linear models are widely applied to capture postural dynamics. This study quantifies the nonlinearity of human arm postural dynamics applying 2D continuous force perturbations (0.2-40 Hz) inducing three levels of hand displacement (5, 15, 45 mm RMS) followed by force-pulse perturbations inducing large hand displacements (up to 250 mm) in a position task (PT) and a relax task (RT) recording activity of eight shoulder and elbow muscles. The continuous perturbation data were used to analyze the 2D endpoint dynamics in the frequency domain and to identify reflexive and intrinsic parameters of a linear neuromuscular shoulder-elbow model. Subsequently, it was assessed to what extent the large displacements in response to force pulses could be predicted from the 'small amplitude' linear neuromuscular model. Continuous and pulse perturbation responses with varying amplitudes disclosed highly nonlinear effects. In PT, a larger continuous perturbation induced stiffening with a factor of 1.5 attributed to task adaptation evidenced by increased co-contraction and reflexive activity. This task adaptation was even more profound in the pulse responses where reflexes and displacements were strongly affected by the presence and amplitude of preceding continuous perturbations. In RT, a larger continuous perturbation resulted in yielding with a factor of 3.8 attributed to nonlinear mechanical properties as no significant reflexive activity was found. Pulse perturbations always resulted in yielding where a model fitted to the preceding 5-mm continuous perturbations predicted only 37% of the recorded peak displacements in RT and 79% in PT. This demonstrates that linear neuromuscular models, identified using continuous perturbations with small amplitudes, strongly underestimate displacements in pulse-shaped (e.g., impact) loading conditions. The data will be used to validate neuromuscular models including nonlinear muscular (e.g., Hill and Huxley) and reflexive components.

Perturbation-evoked responses in primary motor cortex are modulated by behavioral context

Corrective responses to external perturbations are sensitive to the behavioral task being performed. It is believed that primary motor cortex (M1) forms part of a transcortical pathway that contributes to this sensitivity. Previous work has identified two distinct phases in the perturbation response of M1 neurons, an initial response starting ∼20 ms after perturbation onset that does not depend on the intended motor action and a task-dependent response that begins ∼40 ms after perturbation onset. However, this invariant initial response may reflect ongoing postural control or a task-independent response to the perturbation. The present study tested these two possibilities by examining if being engaged in an ongoing postural task before perturbation onset modulated the initial perturbation response in M1. Specifically, mechanical perturbations were applied to the shoulder and/or elbow while the monkey maintained its hand at a central target or when it was watching a movie and not required to respond to the perturbation. As expected, corrective movements, muscle stretch responses, and M1 population activity in the late perturbation epoch were all significantly diminished in the movie task. Strikingly, initial perturbation responses (<40 ms postperturbation) remained the same across tasks, suggesting that the initial phase of M1 activity constitutes a task-independent response that is sensitive to the properties of the mechanical perturbation but not the goal of the ongoing motor task.

Motor cortex single-neuron and population contributions to compensation for multiple dynamic force fields

To elucidate how primary motor cortex (M1) neurons contribute to the performance of a broad range of different and even incompatible motor skills, we trained two monkeys to perform single-degree-of-freedom elbow flexion/extension movements that could be perturbed by a variety of externally generated force fields. Fields were presented in a pseudorandom sequence of trial blocks. Different computer monitor background colors signaled the nature of the force field throughout each block. There were five different force fields: null field without perturbing torque, assistive and resistive viscous fields proportional to velocity, a resistive elastic force field proportional to position and a resistive viscoelastic field that was the linear combination of the resistive viscous and elastic force fields. After the monkeys were extensively trained in the five field conditions, neural recordings were subsequently made in M1 contralateral to the trained arm. Many caudal M1 neurons altered their activity systematically across most or all of the force fields in a manner that was appropriate to contribute to the compensation for each of the fields. The net activity of the entire sample population likewise provided a predictive signal about the differences in the time course of the external forces encountered during the movements across all force conditions. The neurons showed a broad range of sensitivities to the different fields, and there was little evidence of a modular structure by which subsets of M1 neurons were preferentially activated during movements in specific fields or combinations of fields.

Beyond muscles stiffness: importance of state-estimation to account for very fast motor corrections

Feedback delays are a major challenge for any controlled process, and yet we are able to easily control limb movements with speed and grace. A popular hypothesis suggests that the brain largely mitigates the impact of feedback delays (∼50 ms) by regulating the limb intrinsic visco-elastic properties (or impedance) with muscle co-contraction, which generates forces proportional to changes in joint angle and velocity with zero delay. Although attractive, this hypothesis is often based on estimates of limb impedance that include neural feedback, and therefore describe the entire motor system. In addition, this approach does not systematically take into account that muscles exhibit high intrinsic impedance only for small perturbations (short-range impedance). As a consequence, it remains unclear how the nervous system handles large perturbations, as well as disturbances encountered during movement when short-range impedance cannot contribute. We address this issue by comparing feedback responses to load pulses applied to the elbow of human subjects with theoretical simulations. After validating the model parameters, we show that the ability of humans to generate fast and accurate corrective movements is compatible with a control strategy based on state estimation. We also highlight the merits of delay-uncompensated robust control, which can mitigate the impact of internal model errors, but at the cost of slowing feedback corrections. We speculate that the puzzling observation of presynaptic inhibition of peripheral afferents in the spinal cord at movement onset helps to counter the destabilizing transition from high muscle impedance during posture to low muscle impedance during movement.

Context-dependent inhibition of unloaded muscles during the long-latency epoch

A number of studies have highlighted the sophistication of corrective responses in lengthened muscles during the long-latency epoch. However, in various contexts, unloading can occur, which requires corrective actions from a shortened muscle. Here, we investigate the sophistication of inhibitory responses in shortened muscles due to unloading. Our first experiment quantified the inhibitory responses following an unloading torque that displaced the hand either into or away from a peripheral target. We observed larger long-latency inhibitory responses when perturbed into the peripheral target compared with away from the target. In our second experiment, we characterized the degree of inhibition following unloading with respect to different levels of preperturbation muscle activity. We initially observed that the inhibitory activity during the short-latency epoch scaled with increased levels of preperturbation muscle activity. However, this scaling peaked early in the R2 epoch (∼ 50 ms) but then quickly diminished through the rest of the long-latency epoch. Finally, in experiment 3, we investigated whether inhibitory perturbation responses consider intersegmental dynamics of the limb. We quantified unloading responses for either pure shoulder or pure elbow torques that evoked similar motion at the shoulder but different elbow motion. The long-latency inhibitory response in the shoulder, unlike the short-latency, was greater for the shoulder torque compared with the response following an elbow torque, as previously observed for a loading response. Taken together, these results illustrate that the long-latency unloading response is capable of a similar level of complexity as observed when loads are applied to the limb.

Primary motor cortex and fast feedback responses to mechanical perturbations: a primer on what we know now and some suggestions on what we should find out next

Many researchers have drawn a clear distinction between fast feedback responses to mechanical perturbations (e.g., stretch responses) and voluntary control processes. But this simple distinction is difficult to reconcile with growing evidence that long-latency stretch responses share most of the defining capabilities of voluntary control. My general view—and I believe a growing consensus—is that the functional similarities between long-latency stretch responses and voluntary control processes can be readily understood based on their shared neural circuitry, especially a transcortical pathway through primary motor cortex. Here I provide a very brief and selective account of the human and monkey studies linking a transcortical pathway through primary motor cortex to the generation and functional sophistication of the long-latency stretch response. I then lay out some of the notable issues that are ready to be answered.

Biting intentions modulate digastric reflex responses to sudden unloading of the jaw

Reflex responses in jaw-opening muscles can be evoked when a brittle object cracks between the teeth and suddenly unloads the jaw. We hypothesized that this reflex response is flexible and, as such, is modulated according to the instructed goal of biting through an object. Study participants performed two different biting tasks when holding a peanut half stacked on a chocolate piece between their incisors. In one task, they were asked to split the peanut half only (single-split task), and in the other task, they were asked to split both the peanut and the chocolate in one action (double-split task). In both tasks, the peanut split evoked a jaw-opening muscle response, quantified from electromyogram (EMG) recordings of the digastric muscle in a window 20-60 ms following peanut split. Consistent with our hypothesis, we found that the jaw-opening muscle response in the single-split trials was about twice the size of the jaw-opening muscle response in the double-split trials. A linear model that predicted the jaw-opening muscle response on a single-trial basis indicated that task settings played a significant role in this modulation but also that the presplit digastric muscle activity contributed to the modulation. These findings demonstrate that, like reflex responses to mechanical perturbations in limb muscles, reflex responses in jaw muscles not only show gain-scaling but also are modulated by subject intent.

Fractionation of the visuomotor feedback response to directions of movement and perturbation

Recent studies have highlighted the modulation and control of feedback gains as support for optimal feedback control. While many experiments contrast feedback gains across different environments, only a few have demonstrated the appropriate modulation of feedback gains from one movement to the next. Here we extend previous work by examining whether different visuomotor feedback gains can be learned for different directions of movement or perturbation directions in the same posture. To do this we measure visuomotor responses (involuntary motor responses to shifts in the visual feedback of the hand) during reaching movements. Previous work has demonstrated that these feedback responses can be modulated depending on the statistical distributions of the environment. Specifically, feedback gains were upregulated for task-relevant environments and downregulated for task-irrelevant environments. Using these two statistical distributions, the first experiment examined whether these feedback responses could be independently modulated for the same limb posture for two directions of movement (same limb posture but on either an inward or outward movement), while the second examined whether the feedback responses could modulate, within a single movement, to perturbations to the left or right of the reach. Both experiments demonstrated that visuomotor feedback responses could be learned independently such that the response was appropriate for the environment. This work demonstrates that feedback gains can be simultaneously tuned (upregulated and downregulated) depending on the state of the body and the environment. The results indicate the degree to which feedback responses can be fractionated in order to adapt to the world.

Goal-dependent modulation of fast feedback responses in primary motor cortex

Many human studies have demonstrated that rapid motor responses (i.e., muscle-stretch reflexes) to mechanical perturbations can be modified by a participant's intended response. Here, we used a novel experimental paradigm to investigate the neural mechanisms that underlie such goal-dependent modulation. Two monkeys positioned their hand in a central area against a constant load and responded to mechanical perturbations by quickly placing their hand into visually defined spatial targets. The perturbation was chosen to excite a particular proximal arm muscle or isolated neuron in primary motor cortex and two targets were placed so that the hand was pushed away from one target (OUT target) and toward the other (IN target). We chose these targets because they produced behavioral responses analogous to the classical verbal instructions used in human studies. A third centrally located target was used to examine responses with a constant goal. Arm muscles and neurons robustly responded to the perturbation and showed clear goal-dependent responses ∼35 and 70 ms after perturbation onset, respectively. Most M1 neurons and all muscles displayed larger perturbation-related responses for the OUT target than the IN target. However, a substantial number of M1 neurons showed more complex patterns of target-dependent modulation not seen in muscles, including greater activity for the IN target than the OUT target, and changes in target preference over time. Together, our results reveal complex goal-dependent modulation of fast feedback responses in M1 that are present early enough to account for goal-dependent stretch responses in arm muscles.

Rapid online selection between multiple motor plans

Recent theories of voluntary control predict that multiple motor strategies can be precomputed and expressed throughout movement. We examined online decisional processing in humans by asking them to make reaching movements with obstacles located just to the sides of a direct path between start and end targets. On random trials, the limb was perturbed with one of four mechanical loads that varied in direction and amplitude. Notably, we observed two different strategies when we applied a perturbation (left medium-sized) that deviated the participants' hand directly toward an obstacle. In some trials, subjects directed their hand between the obstacles and in other trials to the left of the obstacles. Importantly, changes in the muscle stretch response between these two strategies were observed in <60 ms after perturbation, during the R2 long-latency epoch (~45-75 ms). As predicted, the selected strategy depended on the estimated position of the limb when it was perturbed. In our second experiment, we presented either one or three potential goal targets. Movements initially directed to the closest target could be quickly redirected to other potential targets after a perturbation. Differences in muscle stretch responses for redirected movements were observed ~75 ms after perturbation during the R3 long-latency epoch (~75-105 ms). The results show that decisional processes are rapidly implemented during movement execution. In addition, our data suggest a hierarchical process with corrective responses on "how" to attain a behavioral goal expressed during the R2 epoch and responses on "what" goal to attain during the R3 epoch.

Fast feedback control involves two independent processes utilizing knowledge of limb dynamics

Corrective muscle responses occurring 50-100 ms after a mechanical perturbation are tailored to the mechanical features of the limb and its environment. For example, the evoked response by the shoulder's extensor muscle counters an imposed shoulder torque, rather than local shoulder motion, by integrating motion information from the shoulder and elbow appropriate for their dynamic interaction. Previous studies suggest that arm muscle activity within this epoch, alternately termed the R2/3 response, or long-latency reflex, reflects the summed result of two distinct components: an activity-dependent component which scales with the background muscle activity, and a task-dependent component which scales with the required vigor of the behavioral task. Here we examine how the knowledge of limb dynamics expressed during the shoulder muscle's R2/3 epoch is related to these two functional components. Subjects countered torque steps applied to their shoulder and/or elbow under different conditions of background torque and target size to recruit the activity-dependent and task-dependent component in varying degrees. Experiment 1 involved four torque perturbations, two levels of background torques and two target sizes; this design revealed that both background torque and target size impacted the shoulder's R2/3 activity, indicative of knowledge of limb dynamics. Experiment 2 involved two perturbation torques, five levels of background torque and two target sizes; this design demonstrated that the two factors had an independent impact on the R2/3 activity indicative of knowledge of limb dynamics. We conclude that a sophisticated feature of upper limb feedback control reflects the summation of two processes having a common capability.

Rapid feedback responses correlate with reach adaptation and properties of novel upper limb loads

A hallmark of voluntary motor control is the ability to adjust motor patterns for novel mechanical or visuomotor contexts. Recent work has also highlighted the importance of feedback for voluntary control, leading to the hypothesis that feedback responses should adapt when we learn new motor skills. We tested this prediction with a novel paradigm requiring that human subjects adapt to a viscous elbow load while reaching to three targets. Target 1 required combined shoulder and elbow motion, target 2 required only elbow motion, and target 3 (probe target) required shoulder but no elbow motion. This simple approach controlled muscle activity at the probe target before, during, and after the application of novel elbow loads. Our paradigm allowed us to perturb the elbow during reaching movements to the probe target and identify several key properties of adapted stretch responses. Adapted long-latency responses expressed (de-) adaptation similar to reaching errors observed when we introduced (removed) the elbow load. Moreover, reaching errors during learning correlated with changes in the long-latency response, showing subjects who adapted more to the elbow load displayed greater modulation of their stretch responses. These adapted responses were sensitive to the size and direction of the viscous training load. Our results highlight an important link between the adaptation of feedforward and feedback control and suggest a key part of motor adaptation is to adjust feedback responses to the requirements of novel motor skills.

Decreased fibularis reflex response during inversion perturbations in FAI subjects

Investigate reflex responses in muscles throughout the lower limb and low back during sudden inversion perturbations in individuals with and without Functional Ankle Instability (FAI) while walking. Forty subjects participated in the study. Surface electromyogram recordings were obtained from the fibularis (FIB), gluteus medius (GM), erector spinae (ES), and sternocleidomastoid (SCM) of the injured/matched side as well as the uninjured/matched contralateral side (FIB_CLS, GM_CLS, or ES_CLS). Latency and amplitude data were collected while subjects were walking on a custom-built perturbation walkway. The onset of the short-latency stretch reflex of the FIB was significantly later in the injured side of the FAI individuals when compared to the control group (P=0.009). Both the short and long latency reflex amplitude was significantly smaller in the FIB muscle in the FAI group than in the control group (P<0.008). No significant differences in latency or amplitude reflex responses were identified between the two groups in the GM, ES, FIB_CLS, GM_CLS, or ES_CLS (P>.05). Interpretation of these results indicate that during a dynamic perturbation task individuals with FAI demonstrate longer fibularis muscle latencies on the injured side while no significant changes in the proximal muscle groups. Additionally, short and long latency reflex amplitude was significantly decreased in FAI individuals.

Feedback responses rapidly scale with the urgency to correct for external perturbations

Healthy subjects can easily produce voluntary actions at different speeds and with varying accuracy requirements. It remains unknown whether rapid corrective responses to mechanical perturbations also possess this flexibility and, thereby, contribute to the capability expressed in voluntary control. Paralleling previous studies on self-initiated movements, we examined how muscle activity was impacted by either implicit or explicit criteria affecting the urgency to respond to the perturbation. Participants maintained their arm position against torque perturbations with unpredictable timing and direction. In the first experiment, the urgency to respond was explicitly altered by varying the time limit (300 ms vs. 700 ms) to return to a small target. A second experiment addresses implicit urgency criteria by varying the radius of the goal target, such that task accuracy could be achieved with less vigorous corrections for large targets than small target. We show that muscle responses at ∼60 ms scaled with the task demand. Moreover, in both experiments, we found a strong intertrial correlation between long-latency responses (∼50–100 ms) and the movement reversal times, which emphasizes that these rapid motor responses are directly linked to behavioral performance. The slopes of these linear regressions were sensitive to the experimental condition during the long-latency and early voluntary epochs. These findings suggest that feedback gains for very rapid responses are flexibly scaled according to task-related urgency.

Instruction-dependent modulation of the long-latency stretch reflex is associated with indicators of startle

Long-latency responses elicited by postural perturbation are modulated by how a subject is instructed to respond to the perturbation, yet the neural pathways responsible for this modulation remain unclear. The goal of this study was to determine whether instruction-dependent modulation is associated with activity in brainstem pathways contributing to startle. Our hypothesis was that elbow perturbations can evoked startle, indicated by activity in the sternocleidomastoid muscle (SCM). Perturbation responses were compared to those elicited by a loud acoustic stimulus, known to elicit startle. Postural perturbations and startling acoustic stimuli both evoked SCM activity, but only when a ballistic elbow extension movement was planned. Both stimuli triggered SCM activity with the same probability. When SCM activity was present, there was an associated early onset of triceps electromyographic (EMG), as required for the planned movement. This early EMG onset occurred at a time often attributed to long-latency stretch reflexes (75-100 ms). The nature of the perturbation-triggered EMG (excitatory or inhibitory) was independent of the perturbation direction (flexion or extension) indicating that it was not a feedback response appropriate for returning the limb to its original position. The net EMG response to perturbations delivered after a movement had been planned could be explained as the sum of a stretch reflex opposing the perturbation and a startle-evoked response associated with the prepared movement. These results demonstrate that rapid perturbations can trigger early release of a planned ballistic movement, and that this release is associated with activity in the brainstem pathways contributing to startle reflexes.

Long-latency muscle activity reflects continuous, delayed sensorimotor feedback of task-level and not joint-level error

In both the upper and lower limbs, evidence suggests that short-latency electromyographic (EMG) responses to mechanical perturbations are modulated based on muscle stretch or joint motion, whereas long-latency responses are modulated based on attainment of task-level goals, e.g., desired direction of limb movement. We hypothesized that long-latency responses are modulated continuously by task-level error feedback. Previously, we identified an error-based sensorimotor feedback transformation that describes the time course of EMG responses to ramp-and-hold perturbations during standing balance (Safavynia and Ting 2013; Welch and Ting 2008, 2009). Here, our goals were 1) to test the robustness of the sensorimotor transformation over a richer set of perturbation conditions and postural states; and 2) to explicitly test whether the sensorimotor transformation is based on task-level vs. joint-level error. We developed novel perturbation trains of acceleration pulses such that perturbations were applied when the body deviated from the desired, upright state while recovering from preceding perturbations. The entire time course of EMG responses (∼4 s) in an antagonistic muscle pair was reconstructed using a weighted sum of center of mass (CoM) kinematics preceding EMGs at long-latency delays (∼100 ms). Furthermore, CoM and joint kinematic trajectories became decorrelated during perturbation trains, allowing us to explicitly compare task-level vs. joint feedback in the same experimental condition. Reconstruction of EMGs was poorer using joint kinematics compared with CoM kinematics and required unphysiologically short (∼10 ms) delays. Thus continuous, long-latency feedback of task-level variables may be a common mechanism regulating long-latency responses in the upper and lower limbs.

Common muscle synergies for balance and walking

Little is known about the integration of neural mechanisms for balance and locomotion. Muscle synergies have been studied independently in standing balance and walking, but not compared. Here, we hypothesized that reactive balance and walking are mediated by a common set of lower-limb muscle synergies. In humans, we examined muscle activity during multidirectional support-surface perturbations during standing and walking, as well as unperturbed walking at two speeds. We show that most muscle synergies used in perturbations responses during standing were also used in perturbation responses during walking, suggesting common neural mechanisms for reactive balance across different contexts. We also show that most muscle synergies using in reactive balance were also used during unperturbed walking, suggesting that neural circuits mediating locomotion and reactive balance recruit a common set of muscle synergies to achieve task-level goals. Differences in muscle synergies across conditions reflected differences in the biomechanical demands of the tasks. For example, muscle synergies specific to walking perturbations may reflect biomechanical challenges associated with single limb stance, and muscle synergies used during sagittal balance recovery in standing but not walking were consistent with maintaining the different desired center of mass motions in standing vs. walking. Thus, muscle synergies specifying spatial organization of muscle activation patterns may define a repertoire of biomechanical subtasks available to different neural circuits governing walking and reactive balance and may be recruited based on task-level goals. Muscle synergy analysis may aid in dissociating deficits in spatial vs. temporal organization of muscle activity in motor deficits. Muscle synergy analysis may also provide a more generalizable assessment of motor function by identifying whether common modular mechanisms are impaired across the performance of multiple motor tasks.

Rapid feedback corrections during a bimanual postural task

An important observation in motor physiology is that even the fastest feedback responses can be modified in a task-dependent manner. However, whether or not such responses in one limb can be modulated based on online sensory feedback from other limbs is still unknown. We tested this using a bimanual postural control task, in which the two hands either controlled two separate cursors (double-cursor task) or a single cursor displayed at the spatial average between the hands (single-cursor task). In the first experiment, the two hands were symmetrically perturbed outwards. In the double-cursor task, the participants therefore had to return their hands to the targets, whereas in the single-cursor task no correction was necessary. Within 50 ms, the electromyographic activity showed significantly smaller responses in the single- compared with the double-cursor task. In the second experiment, the perturbation direction of the left hand (inward/outward) was randomized, such that participants could not preplan their response before perturbation onset. Results show that the behavior of the right arm in the one-cursor task depended on online feedback coming from the left arm: the muscular response was modulated within 75 ms based on directionally specific information of the left arm. These results suggest that sensory feedback from one limb can quickly modify the perturbation response of another limb in a task-dependent manner.

Influence of the behavioral goal and environmental obstacles on rapid feedback responses

The motor system must consider a variety of environmental factors when executing voluntary motor actions, such as the shape of the goal or the possible presence of intervening obstacles. It remains unknown whether rapid feedback responses to mechanical perturbations also consider these factors. Our first experiment quantified how feedback corrections were altered by target shape, which was either a circular dot or a bar. Unperturbed movements to each target were qualitatively similar on average but with greater dispersion of end point positions when reaching to the bar. On random trials, multijoint torque perturbations deviated the hand left or right. When reaching to a circular target, perturbations elicited corrective movements that were directed straight to the location of the target. In contrast, corrective movements when reaching to a bar were redirected to other locations along the bar axis. Our second experiment quantified whether the presence of obstacles could interfere with feedback corrections. We found that hand trajectories after the perturbations were altered to avoid obstacles in the environment. Importantly, changes in muscle activity reflecting the different target shapes (bar vs. dot) or the presence of obstacles were observed in as little as 70 ms. Such changes in motor responses were qualitatively consistent with simulations based on optimal feedback control. Taken together, these results highlight that long-latency motor responses consider spatial properties of the goal and environment.

Visuomotor feedback gains upregulate during the learning of novel dynamics

At an early stage of learning novel dynamics, changes in muscle activity are mainly due to corrective feedback responses. These feedback contributions to the overall motor command are gradually reduced as feedforward control is learned. The temporary increased use of feedback could arise simply from the large errors in early learning with either unaltered gains or even slightly downregulated gains, or from an upregulation of the feedback gains when feedforward prediction is insufficient. We therefore investigated whether the sensorimotor control system alters feedback gains during adaptation to a novel force field generated by a robotic manipulandum. To probe the feedback gains throughout learning, we measured the magnitude of involuntary rapid visuomotor responses to rapid shifts in the visual location of the hand during reaching movements. We found large increases in the magnitude of the rapid visuomotor response whenever the dynamics changed: both when the force field was first presented, and when it was removed. We confirmed that these changes in feedback gain are not simply a byproduct of the change in background load, by demonstrating that this rapid visuomotor response is not load sensitive. Our results suggest that when the sensorimotor control system experiences errors, it increases the gain of the visuomotor feedback pathways to deal with the unexpected disturbances until the feedforward controller learns the appropriate dynamics. We suggest that these feedback gains are upregulated with increased uncertainty in the knowledge of the dynamics to counteract any errors or disturbances and ensure accurate and skillful movements.

Deliberation in the motor system: reflex gains track evolving evidence leading to a decision

Both decision making and sensorimotor control require real-time processing of noisy information streams. Historically these processes were thought to operate sequentially: cognitive processing leads to a decision, and the outcome is passed to the motor system to be converted into action. Recently, it has been suggested that the decision process may provide a continuous flow of information to the motor system, allowing it to prepare in a graded fashion for the probable outcome. Such continuous flow is supported by electrophysiology in nonhuman primates. Here we provide direct evidence for the continuous flow of an evolving decision variable to the motor system in humans. Subjects viewed a dynamic random dot display and were asked to indicate their decision about direction by moving a handle to one of two targets. We probed the state of the motor system by perturbing the arm at random times during decision formation. Reflex gains were modulated by the strength and duration of motion, reflecting the accumulated evidence in support of the evolving decision. The magnitude and variance of these gains tracked a decision variable that explained the subject's decision accuracy. The findings support a continuous process linking the evolving computations associated with decision making and sensorimotor control.

Optimal feedback control and the long-latency stretch response

There has traditionally been a separation between voluntary control processes and the fast feedback responses which follow mechanical perturbations (i.e., stretch "reflexes"). However, a recent theory of motor control, based on optimal control, suggests that voluntary motor behavior involves the sophisticated manipulation of sensory feedback. We have recently proposed that one implication of this theory is that the long-latency stretch "reflex", like voluntary control, should support a rich assortment of behaviors because these two processes are intimately linked through shared neural circuitry including primary motor cortex. In this review, we first describe the basic principles of optimal feedback control related to voluntary motor behavior. We then explore the functional properties of upper-limb stretch responses, with a focus on how the sophistication of the long-latency stretch response rivals voluntary control. And last, we describe the neural circuitry that underlies the long-latency stretch response and detail the evidence that primary motor cortex participates in sophisticated feedback responses to mechanical perturbations.

Computational mechanisms of sensorimotor control

In order to generate skilled and efficient actions, the motor system must find solutions to several problems inherent in sensorimotor control, including nonlinearity, nonstationarity, delays, redundancy, uncertainty, and noise. We review these problems and five computational mechanisms that the brain may use to limit their deleterious effects: optimal feedback control, impedance control, predictive control, Bayesian decision theory, and sensorimotor learning. Together, these computational mechanisms allow skilled and fluent sensorimotor behavior.

Feedback modulation: a window into cortical function

A recent study demonstrates involvement of primary motor cortex in task-dependent modulation of rapid feedback responses; cortical neurons resolve locally ambiguous sensory information, producing sophisticated responses to disturbances.

Task-dependent coordination of rapid bimanual motor responses

Optimal feedback control postulates that feedback responses depend on the task relevance of any perturbations. We test this prediction in a bimanual task, conceptually similar to balancing a laden tray, in which each hand could be perturbed up or down. Single-limb mechanical perturbations produced long-latency reflex responses ("rapid motor responses") in the contralateral limb of appropriate direction and magnitude to maintain the tray horizontal. During bimanual perturbations, rapid motor responses modulated appropriately depending on the extent to which perturbations affected tray orientation. Specifically, despite receiving the same mechanical perturbation causing muscle stretch, the strongest responses were produced when the contralateral arm was perturbed in the opposite direction (large tray tilt) rather than in the same direction or not perturbed at all. Rapid responses from shortening extensors depended on a nonlinear summation of the sensory information from the arms, with the response to a bimanual same-direction perturbation (orientation maintained) being less than the sum of the component unimanual perturbations (task relevant). We conclude that task-dependent tuning of reflexes can be modulated online within a single trial based on a complex interaction across the arms.

Principles of sensorimotor learning

The exploits of Martina Navratilova and Roger Federer represent the pinnacle of motor learning. However, when considering the range and complexity of the processes that are involved in motor learning, even the mere mortals among us exhibit abilities that are impressive. We exercise these abilities when taking up new activities - whether it is snowboarding or ballroom dancing - but also engage in substantial motor learning on a daily basis as we adapt to changes in our environment, manipulate new objects and refine existing skills. Here we review recent research in human motor learning with an emphasis on the computational mechanisms that are involved.

Descending corticospinal control of intersegmental dynamics

To make an accurate movement, the CNS has to overcome the inherent complexities of the multijoint limb. For example, interaction torques arise when motion of individual arm segments propagates to adjacent segments causing their movement without any muscle contractions. Since these passive joint torques significantly add to the overall torques generated by active muscular contractions, they must be taken into account during planning or execution of goal-directed movements. We investigated the role of the corticospinal tract in compensating for the interaction torques during arm movements in humans. Twelve subjects reached to visual targets with their arm supported by a robotic exoskeleton. Reaching to one target was accompanied by interaction torques that assisted the movement, while reaching to the other target was accompanied by interaction torques that resisted the movement. Corticospinal excitability was assessed at different times during movement using single-pulse transcranial magnetic stimulation (TMS) over the upper-arm region of M1 (primary motor cortex). We found that TMS responses in shoulder monoarticular and elbow-shoulder biarticular muscles changed together with the interaction torques during movements in which the interaction torques were resistive. In contrast, TMS responses did not correlate with assistive interaction torques or with co-contraction. This suggests that the descending motor command includes compensation for passive limb dynamics. Furthermore, our results suggest that compensation for interaction torques involves the biarticular muscles, which span both shoulder and elbow joints and are in a biomechanically advantageous position to provide such compensation.

The long-latency reflex is composed of at least two functionally independent processes

The nervous system counters mechanical perturbations applied to the arm with a stereotypical sequence of muscle activity, starting with the short-latency stretch reflex and ending with a voluntary response. Occurring between these two events is the enigmatic long-latency reflex. Although researchers have been fascinated by the long-latency reflex for over 60 years, some of the most basic questions about this response remain unresolved and often debated. In the present study we help resolve one such question by providing clear evidence that the human long-latency reflex during a naturalistic motor task is not a single functional response; rather, it appears to reflect the output of (at least) two functionally independent processes that overlap in time and sum linearly. One of these functional components shares an important attribute of the short-latency reflex (i.e., automatic gain scaling, sensitivity to background load), and the other shares a defining feature of voluntary control (i.e., task dependency, sensitivity to goal target position). We further show that the task-dependent component of long-latency activity reflects a feedback control process rather than the simplest triggered reaction to a mechanical stimulus.

Colored context cues can facilitate the ability to learn and to switch between multiple dynamical force fields

We tested the efficacy of color context cues during adaptation to dynamic force fields. Four groups of human subjects performed elbow flexion/extension movements to move a cursor between targets on a monitor while encountering a resistive (Vr) or assistive (Va) viscous force field. They performed two training sets of 256 trials daily, for 10 days. The monitor background color changed (red, green) every four successful trials but provided different degrees of force field context information to each group. For the irrelevant-cue groups, the color changed every four trials, but one group encountered only the Va field and the other only the Vr field. For the reliable-cue group, the force field alternated between Va and Vr each time the monitor changed color (Vr, red; Va, green). For the unreliable-cue group, the force field changed between Va and Vr pseudorandomly at each color change. All subjects made increasingly stereotyped movements over 10 training days. Reliable-cue subjects typically learned the association between color cues and fields and began to make predictive changes in motor output at each color change during the first day. Their performance continued to improve over the remaining days. Unreliable-cue subjects also improved their performance across training days but developed a strategy of probing the nature of the field at each color change by emitting a default motor response and then adjusting their motor output in subsequent trials. These findings show that subjects can extract explicit and implicit information from color context cues during force field adaptation.

Long-Latency and Voluntary Responses to an Arm Displacement Can Be Rapidly Attenuated By Perturbation Offset

Feedback control of our limbs must account for the unexpected offset of mechanical perturbations. Here we examine the evoked activity of elbow flexor and extensor muscles to torque pulses lasting 22–152 ms and how torque offset impacts activity in the long-latency (45–100 ms) and voluntary epochs (120–180 ms). For each pulse width, we found a significant attenuation of muscle activity ∼30 ms after the offset of torque compared with when the torque was sustained. The brief time between the offset of torque and the attenuation of muscle activity implicates group I afferents acting through a spinal pathway, because this route is the only one fast enough and short enough to be responsible. Moreover, elbow muscle activity in the subsequent 20–45 ms following torque-offset was ∼35% smaller than when the torque was sustained. These results show that a fast spinal process can powerfully attenuate corrective responses of the arm to a torque perturbation.

Compensations in response to real-time formant perturbations of different magnitudes

Previous auditory perturbation studies have demonstrated that talkers spontaneously compensate for real-time formant-shifts by altering formant production in a manner opposite to the perturbation. Here, two experiments were conducted to examine the effect of amplitude of perturbation on the compensatory behavior for the vowel /epsilon/. In the first experiment, 20 male talkers received three step-changes in acoustic feedback: F1 was increased by 50, 100, and 200 Hz, while F2 was simultaneously decreased by 75, 125, and 250 Hz. In the second experiment, 21 male talkers received acoustic feedback in which the shifts in F1 and F2 were incremented by +4 and -5 Hz on each utterance to a maximum of +350 and -450 Hz, respectively. In both experiments, talkers altered production of F1 and F2 in a manner opposite to that of the formant-shift perturbation. Compensation was approximately 25%-30% of the perturbation magnitude for shifts in F1 and F2 up to 200 and 250 Hz, respectively. As larger shifts were applied, compensation reached a plateau and then decreased. The similarity of results across experiments suggests that the compensatory response is dependent on the perturbation magnitude but not on the rate at which the perturbation is introduced.

Complex spatiotemporal tuning in human upper-limb muscles

Correlations between neural activity in primary motor cortex (M1) and arm kinematics have recently been shown to be temporally extensive and spatially complex. These results provide a sophisticated account of M1 processing and suggest that M1 neurons encode high-level movement trajectories, termed "pathlets." However, interpreting pathlets is difficult because the mapping between M1 activity and arm kinematics is indirect: M1 activity can generate movement only via spinal circuitry and the substantial complexities of the musculoskeletal system. We hypothesized that filter-like complexities of the musculoskeletal system are sufficient to generate temporally extensive and spatially complex correlations between motor commands and arm kinematics. To test this hypothesis, we extended the computational and experimental method proposed for extracting pathlets from M1 activity to extract pathlets from muscle activity. Unlike M1 activity, it is clear that muscle activity does not encode arm kinematics. Accordingly, any spatiotemporal correlations in muscle pathlets can be attributed to musculoskeletal complexities rather than explicit higher-order representations. Our results demonstrate that extracting muscle pathlets is a robust and repeatable process. Pathlets extracted from the same muscle but different subjects or from the same muscle on different days were remarkably similar and roughly appropriate for that muscle's mechanical action. Critically, muscle pathlets included extensive spatiotemporal complexity, including kinematic features before and after the present muscle activity, similar to that reported for M1 neurons. These results suggest the possibility that M1 pathlets at least partly reflect the filter-like complexities of the periphery rather than high-level representations.

Interactions between limb and environmental mechanics influence stretch reflex sensitivity in the human arm

Stretch reflexes contribute to arm impedance and longer-latency stretch reflexes exhibit increased sensitivity during interactions with compliant or unstable environments. This increased sensitivity is consistent with a regulation of arm impedance to compensate for decreased stability of the environment, but the specificity of this modulation has yet to be investigated. Many tasks, such as tool use, compromise arm stability along specific directions, and stretch reflexes tuned to those directions could present an efficient mechanism for regulating arm impedance in a task-appropriate manner. To be effective, such tuning should adapt not only to the mechanical properties of the environment but to those properties in relation to the arm, which also has directionally specific mechanical properties. The purpose of this study was to investigate the specificity of stretch reflex modulation during interactions with mechanical environments that challenge arm stability. The tested environments were unstable, having the characteristics of a negative stiffness spring. These were either aligned or orthogonal to the direction of maximal endpoint stiffness for each subject. Our results demonstrate preferential increases in reflexes, elicited within 50-100 ms of perturbation onset, to perturbations applied specifically along the direction of the destabilizing environments. This increase occurred only when the magnitude of the environmental instability exceeded endpoint stiffness along the same direction. These results are consistent with task-specific reflex modulation tuned to the mechanical properties of the environment relative to those of the human arm. They demonstrate a highly adaptable, involuntary mechanism that may be used to modulate limb impedance along specific directions.

Long-Latency Responses During Reaching Account for the Mechanical Interaction Between the Shoulder and Elbow Joints

Although considerable research indicates that reaching movements rely on knowledge of the arm's mechanical properties and environment to anticipate and counter predictable loads, far less research has examined whether this degree of sophistication is present for on-line corrections during reaching. Here we examine the R2/3 response to mechanical perturbations (45–100 ms, also called the long-latency reflex), which is highly flexible and includes the fastest possible contribution from primary motor cortex, a key neural substrate for self-initiated action. Torque perturbations were occasionally and unexpectedly applied to the subject's shoulder and/or elbow in the course of performing reaching movements. Critically, these perturbations would evoke different patterns of feedback corrections from a shoulder extensor muscle if it countered only the local shoulder displacement relative to unperturbed motion or accounted for the mechanical interactions between the shoulder and elbow joints and countered the underlying shoulder torque. Our results show that the earliest response (R1: 20–45 ms) reflected local shoulder displacement, whereas the R2/3 response (45–100 ms) reflected knowledge of multijoint dynamics. Moreover, the same pattern of feedback occurred whether the shoulder muscle helped initiate the movement (during its agonist phase) or helped terminate the movement (during its antagonist phase). These results contribute to the accumulating evidence that highly sophisticated feedback control underlies motor behavior and are consistent with a shared neural substrate, such as primary motor cortex, for feedforward and feedback control.